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Senior Llm Engineer Jobs in Indiana (NOW HIRING)

Parloa

Senior Agent Architect

Florence, IN

You will also shape the conversational experience layer, using prompt engineering and your ... Use your knowledge of LLM internals (e.g., embeddings) to analyze customer requirements and design ...

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Senior Llm Engineer information

What are the key skills and qualifications needed to thrive as a senior LLM engineer, and why are they important?

To thrive as a Senior LLM Engineer, you need deep expertise in machine learning, natural language processing, and advanced programming skills, typically supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as PyTorch, TensorFlow, Hugging Face Transformers, and cloud platforms, along with experience in deploying large-scale language models, is crucial. Strong problem-solving, collaboration, and communication skills set top performers apart in leading cross-functional AI initiatives. These abilities are vital for developing, optimizing, and scaling cutting-edge language models that drive innovation and business value.

Are senior Llm engineers in demand?

Senior Llm engineers are in high demand due to the rapid growth of artificial intelligence and natural language processing industries. They are sought after for their expertise in developing and deploying large language models, often requiring skills in machine learning frameworks, programming, and data management. This demand is expected to continue as AI applications expand across various sectors.

What is a senior LLM engineer?

Senior LLM (Large Language Model) Engineers are experienced professionals who design, build, optimize, and maintain advanced language models like GPT, BERT, or similar AI systems. They work on tasks such as model training, fine-tuning, deployment, and troubleshooting, often collaborating with data scientists and software engineers. Their expertise includes deep learning frameworks, natural language processing, and software engineering best practices. Senior LLM Engineers also play a key role in ensuring the ethical and efficient use of AI models in production systems.

What are some common challenges senior LLM engineers face when deploying large language models in production environments?

Senior LLM Engineers often encounter challenges related to scaling models efficiently, managing latency, and ensuring model outputs are safe and reliable. Deploying large language models requires careful optimization to balance performance with computational costs, as well as robust monitoring to detect and mitigate issues like bias or hallucination in outputs. Collaboration with cross-functional teams, including data scientists, product managers, and DevOps, is key to addressing these challenges and ensuring successful model deployment and maintenance.

What is the difference between Senior Llm Engineer vs Machine Learning Engineer?

AspectSenior Llm EngineerMachine Learning Engineer
CredentialsAdvanced degrees in CS, NLP, or AI; experience with LLMsDegrees in CS, Data Science, or AI; strong programming skills
Work EnvironmentFocus on NLP, language models, and large-scale data processingBroader ML tasks, including data modeling, algorithms, and deployment
Industry UsagePrimarily in AI/NLP-focused companies, research labs

Senior Llm Engineers specialize in large language models and NLP-specific tasks, often requiring advanced NLP knowledge and experience with LLMs. Machine Learning Engineers have a broader scope, working on various ML models and applications across industries. While both roles require strong technical skills, Senior Llm Engineers focus more on language-specific AI, whereas Machine Learning Engineers handle diverse ML projects.

What are the most commonly searched types of Llm Engineer jobs in Indiana?

The most popular types of Llm Engineer jobs in Indiana are:

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Senior Llm Engineer jobs near you

Forward Deployed Engineer - Databricks

Deloitte

Indianapolis, IN

Full-time

Re-posted 6 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services

Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on September 30, 2026

Work you'll do

As a Databricks FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Databricks including hands on experience with one of the following key platform technologies; DBRX, MLflow, Vector Search, Databricks AI Gateway
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on September 30, 2026

Work you'll do

As a Databricks FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Databricks including hands on experience with one of the following key platform technologies; DBRX, MLflow, Vector Search, Databricks AI Gateway
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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